This work addresses maximally robust control synthesis under unknown disturbances. We consider a nonlinear system, subject to a Signal Temporal Logic (STL) specification and jointly synthesize the maximal possible dis...
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This research paper provides an extensive examination of electromagnetic interference (EMI) in wireline transceiver systems. Wireline transceiver circuits are particularly susceptible to undesired electromagnetic wave...
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Computational screening of naturally occurring proteins has the potential to identify efficient catalysts among the hundreds of millions of sequences that remain uncharacterized. Current experimental methods remain ti...
Computational screening of naturally occurring proteins has the potential to identify efficient catalysts among the hundreds of millions of sequences that remain uncharacterized. Current experimental methods remain time, cost and labor intensive, limiting the number of enzymes they can reasonably screen. In this work, we propose a computational framework for in silico enzyme screening. Through a contrastive objective, we train CLIPZyme to encode and align representations of enzyme structures and reaction pairs. With no standard computational baseline, we compare CLIPZyme to existing EC (enzyme commission) predictors applied to virtual enzyme screening and show improved performance in scenarios where limited information on the reaction is available (BEDROC85 of 44.69%). Additionally, we evaluate combining EC predictors with CLIPZyme and show its generalization capacity on both unseen reactions and protein clusters. Copyright 2024 by the author(s)
Sampling-based path planning is widely used in robotics,particularly in high-dimensional state *** the path planning process,collision detection is the most time-consuming ***,we propose a learning-based path planning...
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Sampling-based path planning is widely used in robotics,particularly in high-dimensional state *** the path planning process,collision detection is the most time-consuming ***,we propose a learning-based path planning method that reduces the number of collision *** develop an efficient neural network model based on graph neural *** model outputs weights for each neighbor based on the obstacle,searched path,and random geometric graph,which are used to guide the planner in avoiding *** evaluate the efficiency of the proposed path planning method through simulated random worlds and real-world *** results demonstrate that the proposed method significantly reduces the number of collision checks and improves the path planning speed in high-dimensional environments.
A capacitive touch panel (CTP) is one of most important applications that is used in most of the human controlled electronic devices. The sensor detects CTP and decide if there is error or not. The error might be caus...
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The great challenges faced by modern power systems require a fresh look at the conventional operation paradigm. The significant challenges faced by modern power systems require an innovative method for the conventiona...
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The great challenges faced by modern power systems require a fresh look at the conventional operation paradigm. The significant challenges faced by modern power systems require an innovative method for the conventional operation paradigm. We claim that the decarbonization of the power grid and extensive electrification of numerous sectors of human activity can only be fostered by a self-adaptable and smart power grid that manifests similar qualities to those of the Internet. The Internet is constructed on a layered architecture that facilitates technology innovations and its intelligence is distributed throughout a hierarchy of networks. In this paper, the fundamental differences between the network data flows and power flows are examined, and the basic requirements for an innovative operation paradigm are highlighted. The current power grid is operated in a highly inflexible, centralized manner to meet increased security goals. A new highly flexible, distributed architecture can be realized by distributing the operation responsibility in smaller areas or even in grid components that can make autonomous decisions. The characteristics of such a power grid are presented, and the key features and advances for the on-going transition to a sustainable power system are identified. Finally, a case study on distributed voltage control is presented and discussed.
In this work, we present a novel risk-aware decentralized Control Barrier Function (CBF)-based controller for multi-agent systems. The proposed decentralized controller is composed based on pairwise agent responsibili...
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Photonic Random-Access Memories(P-RAM)are an essential component for the on-chip non-von Neumann photonic computing by eliminating optoelectronic conversion losses in data *** Phase-Change Materials(PCMs)have been sho...
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Photonic Random-Access Memories(P-RAM)are an essential component for the on-chip non-von Neumann photonic computing by eliminating optoelectronic conversion losses in data *** Phase-Change Materials(PCMs)have been showed multilevel memory capability,but demonstrations still yield relatively high optical loss and require cumbersome WRITE-ERASE approaches increasing power consumption and system package *** we demonstrate a multistate electrically programmed low-loss nonvolatile photonic memory based on a broadband transparent phase-change material(Ge2Sb2Se5,GSSe)with ultralow absorption in the amorphous state.A zero-staticpower and electrically programmed multi-bit P-RAM is demonstrated on a silicon-on-insulator platform,featuring efficient amplitude modulation up to 0.2 dB/μm and an ultralow insertion loss of total 0.12 dB for a 4-bit memory showing a 100×improved signal to loss ratio compared to other phase-change-materials based photonic *** further optimize the positioning of dual microheaters validating performance *** we demonstrate a half-a-million cyclability test showcasing the robust approach of this material and ***-loss photonic retention-of-state adds a key feature for photonic functional and programmable circuits impacting many applications including neural networks,LiDAR,and sensors for example.
Reconfigurable intelligent surfaces (RIS) have gained widespread application in the field of communications and are gradually extending their utility to the radar domain. This paper focuses on a mono-static RIS-assist...
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This paper proposes a Human Intelligence (HI)-based Computational Intelligence (CI) and Artificial Intelligence (AI) Fuzzy Markup Language (CI&AI-FML) Metaverse as an educational environment for co-learning of stu...
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